main

通常语音信号在增强时会出现混响现象，演讲者为了消除背景混响，不得不频繁地偏转头部的方向，这样会造成脉冲响应的不断改变。我们结合盲解卷法和频谱消去法来提高逆滤波器的滤波效果。我们利用输入语音信号间的相关系数矩阵计算出稳定、精确的室内脉冲响应的逆滤波器，而这些输入信号无需测量室内的脉冲响应就能被观测到。逆滤波能够消除早期的反射，这些反射包含混响中的绝大部分能量。之后，用频谱消去法来抑制逆滤波后的信号的尾部混响。本方法在实际适应性方面的表现通过具体的实验进行了验证，结果表明盲解卷法和频谱消去法的结合相较于单独使用一种方法，能够提供一个更优越的演说环境。(Usually voice signal will be enhanced when the reverberation phenomenon, the speaker in order to eliminate the background reverberation, and had to frequently deflect the direction of the head, this will cause the impulse response of changing. We combine the blind deconvolution and spectral elimination method to improve the filtering effect of the inverse filter. We use the correlation coefficient matrix between the input speech signal to calculate the stable, accurate inverse filter of the indoor impulse response, and these input signals do not need to measure the room impulse response can be observed. Inverse filtering to eliminate early reflections, these reflections contains most of the energy in the reverberation. After the spectrum elimination method to suppress the tail reverberation of the signal after the inverse filtering. Performance in the actual adaptation of the method by specific experimental validation results show that the blind deconvolution and spectrum to eliminate )

System Time Modifier ModifySysTimeItem

产生双音多频信号。输入任何参数就可得到所要的结果。(Generate DTMF signal. Input any parameters, you will get what you need.)

基于LMS(最小均方误差算法)的自适应滤波 基于LMS(最小均方误差算法)的自适应滤波(based on the LMS (MMSE) algorithm based on the LMS adaptive filtering (minimum mean square error algorithm) the adaptive filtering based on the LMS (minimum mean square error algorithm) Adaptive Filter)

实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)

实现多个人的说话人识别，基于gmm模型，用mfcc参数训练(voice conversion based on gmm)

这是语音信号处理中求倒谱的程序,我自己编的,很简单,实现了一段序列求倒谱的功能(This is the voice signal processing for cepstrum procedures, I developed, is very simple. achieve a sequence for the functional cepstrum)

一种改进的DTW语音识别算法,可以加快识别速度.(An improved DTW speech recognition algorithm, can accelerate the recognition speed.)

西奥多里蒂斯著，李晶皎译 本书系统阐述了模式识别的原理与方法，并在此基础上介绍了模式识别的应用。全书分为：基础部分和应用部分：基础部分主要包括统计模式识别、模糊模式识别、神经网络模式识别等内容；应用部分有车牌识别和语音识别。 (This paper discussed the principles and methods of pattern recognition, and based on this, the application of pattern recognition. Encyclopedia is divided into: basic part and application part: basic parts mainly include statistical pattern recognition, the fuzzy pattern recognition, neural network pattern recognition content Application part have license plate identification and voice recognition.)

simple voice recognition program